Data-driven Networking Reveals 5-Genes Signature for Early Detection of Lung Cancer

A new strategy is developed for a gene signature search proceeding from a biological basis in analyzing microarray databases. The procedure involves a combination of known and original methods for correlation, statistical, and network analysis. The application of the strategy to lung adenocarcinoma resulted in a 5-gene signature, which included four genes not associated earlier with lung adenocarcinoma. 93-96% accuracy of classification of cancer vs. normal was achieved. The final stage of our procedure included expanding of the gene signature network to a 43 gene/protein network, which showed that the five genes are in the cross-talk of 24 pathways, providing thus information for mechanistic analysis.